Buch, Englisch, Band 3020, 514 Seiten, Format (B × H): 155 mm x 235 mm, Gewicht: 797 g
21st International Conference, IPMU 2026, Rome, Italy, June 15-19, 2026, Proceedings, Part II
Buch, Englisch, Band 3020, 514 Seiten, Format (B × H): 155 mm x 235 mm, Gewicht: 797 g
Reihe: Communications in Computer and Information Science
ISBN: 978-3-032-28996-4
Verlag: Springer
This three-volume set CCIS 3019-3021 constitutes the proceedings of the 21st International Conference on Information Processing and Management of Uncertainty in Knowledge-Based Systems, IPMU 2026, held in Rome, Italy, during June 15-19, 2026.
The 111 full papers included in these volumes were carefully reviewed and selected from 254 submissions. They are organized into topical sections as follows:
Part I: Aggregation theory; Imprecise probabilities; Knowledge representation and modelling; Statistical inference and data analysis.
Part II: Robustness in economics and finance, Foundations of fuzzy sets; Fuzzy and multivalued logic; Explainable AI and decision making.
Part III: Preference modelling; Cooperative automated systems; Fuzzy control: methods and applications; Fuzzy implication functions; Data mining.
Zielgruppe
Research
Autoren/Hrsg.
Fachgebiete
Weitere Infos & Material
.- Robustness in economics and finance.
.- Fuzzy Extensions of SDEs and the Non-Overlap of Crisp and Fuzzy
Solution Trajectories.
.- A fuzzy variational model for spatial innovation diffusion with uncertain
inter-regional influence.
.- A Risk Management Agent with Uncertainty Quantification for
Financial Trading.
.- Credal Ensemble Classification with Structural Discriminative
Gaussian-Bernoulli RBMs.
.- Enforcing Sparsity of Imprecise Transport Plans in Dempster-Shafer
Optimal Transport.
.- On the Calculation and Risk Analysis of Finite Interval Predictors.
.- Foundations of fuzzy sets.
.- New negations for notable restrictions on the membership degrees of
type-2 fuzzy sets.
.- On type reductions with quantale based fuzzy sets .
.- A preliminary study on the use of dCF-integrals in Fuzzy Rule-Based
Classification Systems for Class Imbalance.
.- A duality relationship between similarity metrics and Mathew’s partial
metrics based on boundedness.
.- Representation of quasi-(pesudo-)metrics by means of fuzzy sets.
.- Behaviour of Morphological Operators in L-powersets of Additive
Groups Under Powerset Operators.
.- Penrose-Banzhaf Weighted Aggregation Operator with Sugeno-Weber
t-norms for Intuitionistic Fuzzy Valued Neutrosophic Sets: A Spatial
Multi-Criteria Decision Illustration.
.- Picture Fuzzy Set–Based Approach for Classification.
.- On admisible interval orders and partial metrics on discrete fuzzy numbers.
.- Fuzzy and multivalued logic.
.- Optimizing de Finetti’s Coherence: a Complexity Analysis.
.- On the complexity of the logics of strongly perfect MTL-algebras and
related systems.
.- Quantum-Inspired Fuzzy Committee Optimization for Blockchain
Consensus.
.- Ideally Exact Categories, Varieties of Universal Algebras and
Multi-Valued Logics.
.- Fuzzy Rule-Based Approach for Weighting Artificial Experts involved
in a Multi-Criteria Group Decision-Making Problem.
.- Functors between Fuzzy Varieties.
.- Uncertainty-Aware Graph Integration: A Fuzzy Logic Approach with
Comparative Analysis.
.- On Veracity Handling in Document Stores: A Novel Technique Based on L-graded Logic Running on the J-CO Framework.
.- A Max–Min Neural Network Model for Propositional Fuzzy Logic.
.- Fuzzy and multivalued logic.
.- An Engineering Methodology for Verifying Compliance with the EU AI
Act in Industrial AI Systems.
.- Neural Networks for Non-Convex Lattice Geometry: Extending Stoka’s
Theory with Machine Learning Application to Financial Risk and
Economic Forecasting.
.- Multi-Objective Optimization and Machine Learning Framework for
Tax Risk Management: Theory and Applications.
.- Explainable Uncertainty Quantification for Wastewater Treatment
Energy Prediction via Interval Type-2 Neuro-Fuzzy System.
.- Constraint-Based Reliability Estimation in Sparse and Irregular Time
Series.
.- Automatic Assessment of Node Compromise Risks in Critical
Infrastructures via a Multi-Stage Uncertainty Reduction Model using
LLMs.
.- On Counterfactual Explanations and Adversarial Examples for
Set-Valued Classifiers.
.- Comparative reversal learning reveals rigid adaptation in LLMs under
non-stationary uncertainty .
.- FIRE: Fuzzy Information for Reconstructing Events.
.- Leveraging Causal Graphs to Improve LLM-Based Causal Reasoning:
an Empirical Study.
.- Uncertainty Aware Contextual Recommendation under Possible Worlds
Semantics.
